Polarimetric imaging for the detection of synthetic models of SARS-CoV-2: a proof of concept

Objective To conduct a proof-of-concept study of the detection of two synthetic models of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using polarimetric imaging. Approach Two SARS-CoV-2 models were prepared as engineered lentiviruses pseudotyped with the G protein of the vesicular stomatitis virus, and with the characteristic Spike protein of SARS-CoV-2. Samples were preparations in two biofluids (saline solution and artificial saliva), in four concentrations, and deposited as 5-μL droplets on a supporting plate. The angles of maximal degree of linear polarization (DLP) of light diffusely scattered from dry residues were determined using Mueller polarimetry of 87 samples at 405 nm and 514 nm. A polarimetric camera was used for imaging several samples under 380-420 nm illumination at angles similar to those of maximal DLP. Per-pixel image analysis included quantification and combination of polarization feature descriptors in 475 samples. Main results The angles (from sample surface) of maximal DLP were 3 degrees for 405 nm and 6 degrees for 514 nm. Similar viral particles that differ only in the characteristic spike protein of the SARS-CoV-2, their corresponding negative controls, fluids, and the sample holder were discerned at 10-degree and 15-degree configurations. Significance Polarimetric imaging in the visible spectrum may help improve fast, non-contact detection and identification of viral particles, and/or other microbes such as tuberculosis, in multiple dry fluid samples simultaneously, particularly when combined with other imaging modalities. Further analysis including realistic concentrations of real SARS-CoV-2 virus particles in relevant human fluids is required. Polarimetric imaging under visible light may contribute to fast, cost-effective screening of SARS-CoV-2 and other pathogens.

Polarimetric imaging for the detection of synthetic models of SARS-CoV-2: A proof of concept.

Objective: To conduct a proof-of-concept study of the detection of two synthetic models of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using polarimetric imaging. Approach: Two SARS-CoV-2 models were prepared as engineered lentiviruses pseudotyped with the G protein of the vesicular stomatitis virus, and with the characteristic Spike protein of SARS-CoV-2. Samples were prepared in two biofluids (saline solution and artificial saliva), in four concentrations, and deposited as 5-µL droplets on a supporting plate. The angles of maximal degree of linear polarization (DLP) of light diffusely scattered from dry residues were determined using Mueller polarimetry from87 samples at 405 nm and 514 nm. A polarimetric camera was used for imaging several samples under 380-420 nm illumination at angles similar to those of maximal DLP. Per-pixel image analysis included quantification and combination of polarization feature descriptors in 475 samples. Main results: The angles (from sample surface) of maximal DLP were 3° for 405 nm and 6° for 514 nm. Similar viral particles that differed only in the characteristic spike protein of the SARS-CoV-2, their corresponding negative controls, fluids, and the sample holder were discerned at 10-degree and 15-degree configurations. Significance: Polarimetric imaging in the visible spectrum may help improve fast, non-contact detection and identification of viral particles, and/or other microbes such as tuberculosis, in multiple dry fluid samples simultaneously, particularly when combined with other imaging modalities. Further analysis including realistic concentrations of real SARS-CoV-2 viral particles in relevant human fluids is required. Polarimetric imaging under visible light may contribute to a fast, cost-effective screening of SARS-CoV-2 and other pathogens when combined with other imaging modalities.

COVID-19 contagion forecasting framework based on curve decomposition and evolutionary artificial neural networks: A case study in Andalusia, Spain.

Many types of research have been carried out with the aim of combating the COVID-19 pandemic since the first outbreak was detected in Wuhan, China. Anticipating the evolution of an outbreak helps to devise suitable economic, social and health care strategies to mitigate the effects of the virus. For this reason, predicting the SARS-CoV-2 transmission rate has become one of the most important and challenging problems of the past months. In this paper, we apply a two-stage mid and long-term forecasting framework to the epidemic situation in eight districts of Andalusia, Spain. First, an analytical procedure is performed iteratively to fit polynomial curves to the cumulative curve of contagions. Then, the extracted information is used for estimating the parameters and structure of an evolutionary artificial neural network with hybrid architectures (i.e., with different basis functions for the hidden nodes) while considering single and simultaneous time horizon estimations. The results obtained demonstrate that including polynomial information extracted during the training stage significantly improves the mid- and long-term estimations in seven of the eight considered districts. The increase in average accuracy (for the joint mid- and long-term horizon forecasts) is 37.61% and 35.53% when considering the single and simultaneous forecast approaches, respectively.

Optical imaging spectroscopy for rapid, primary screening of SARS-CoV-2: a proof of concept.

Effective testing is essential to control the coronavirus disease 2019 (COVID-19) transmission. Here we report a-proof-of-concept study on hyperspectral image analysis in the visible and near-infrared range for primary screening at the point-of-care of SARS-CoV-2. We apply spectral feature descriptors, partial least square-discriminant analysis, and artificial intelligence to extract information from optical diffuse reflectance measurements from 5 µL fluid samples at pixel, droplet, and patient levels. We discern preparations of engineered lentiviral particles pseudotyped with the spike protein of the SARS-CoV-2 from those with the G protein of the vesicular stomatitis virus in saline solution and artificial saliva. We report a quantitative analysis of 72 samples of nasopharyngeal exudate in a range of SARS-CoV-2 viral loads, and a descriptive study of another 32 fresh human saliva samples. Sensitivity for classification of exudates was 100% with peak specificity of 87.5% for discernment from PCR-negative but symptomatic cases. Proposed technology is reagent-free, fast, and scalable, and could substantially reduce the number of molecular tests currently required for COVID-19 mass screening strategies even in resource-limited settings.

Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples.

Optical spectroscopic techniques have been commonly used to detect the presence of biofilm-forming pathogens (bacteria and fungi) in the agro-food industry. Recently, near-infrared (NIR) spectroscopy revealed that it is also possible to detect the presence of viruses in animal and vegetal tissues. Here we report a platform based on visible and NIR (VNIR) hyperspectral imaging for non-contact, reagent free detection and quantification of laboratory-engineered viral particles in fluid samples (liquid droplets and dry residue) using both partial least square-discriminant analysis and artificial feed-forward neural networks. The detection was successfully achieved in preparations of phosphate buffered solution and artificial saliva, with an equivalent pixel volume of 4 nL and lowest concentration of 800 TU·[Formula: see text]L-1. This method constitutes an innovative approach that could be potentially used at point of care for rapid mass screening of viral infectious diseases and monitoring of the SARS-CoV-2 pandemic.

Early implementation of protective measures defines surgical outcomes in the COVID-19 pandemic.

Quick implementation of specific protocols and protective measures in a tertiary hospital in Spain allowed for the early diagnosis and optimal management of patients with SARS-CoV-2 infection and proper protection of staff and inpatients. From the COVID-19 outbreak in this country until the time of writing, 14 patients in our hospital underwent surgery with COVID-19, or COVID-19 developed postoperatively. Their postoperative outcomes did not differ from those in our routine clinical practice, with a 0% respiratory failure rate and a 7.14% mortality rate, in contrast with other published series. COVID-19 did not develop in any of the healthcare workers present in the operating room during these procedures or in those who cared for these patients on the ward.